Job description
Credit Strategy Data Scientist
Location: Remote (U.S.-based candidates only) - 12 month contract
Full-Time | MidSenior Level | No Visa Sponsorship or Relocation
Overview
A fast-growing financial services organization is seeking a Credit Strategy Data Scientist to join its high-performing Credit Risk Strategy team. This is an exciting opportunity for a data-savvy professional with fintech or payments industry experience to help drive business-critical decisions through advanced analytics, predictive modeling, and risk mitigation strategies.
You will work on end-to-end development of data-driven credit solutionspartnering closely with cross-functional stakeholders to design, execute, and refine credit strategies that support responsible growth and customer success.
What Youll Do
Design and implement data-driven rules to detect and mitigate credit
losses
Investigate complex and high-impact risk cases and identify root causes
Set and refine credit risk strategies across various risk categories
Collaborate with product and engineering teams to enhance risk control capabilities
Lead the development of dashboards, visualizations, and reports to track credit KPIs
Present data-backed recommendations to stakeholders and executives
Use large-scale datasets to uncover patterns and drive risk optimization
Work with RaaS platforms to analyze loss trends and apply strategic adjustments
Must-Have Qualifications
Bachelors degree in Computer Science, Engineering, Mathematics, Statistics, Data Mining, or a related field (or equivalent practical experience)
2+ years of hands-on experience in risk analytics, data science, or data analysispreferably within fintech or online payments
Proficiency in SQL, Python, and Excel, including core data science libraries
Proven ability to work with large datasets and derive actionable insights
Experience developing and communicating dashboards and visualizations (e.g. Tableau)
Strong communication skills and ability to translate complex analysis to diverse audiences
Demonstrated data-driven decision-making and solution development
Preferred Skills & Experience
Experience applying data science to credit risk and loss mitigation problems
Familiarity with AWS, payment rule systems, or credit product lifecycles
Strong project management skills and ability to drive analytics from concept to execution
Comfortable working in fast-paced, ambiguous environments with shifting priorities
Expected Outcomes (6-12 Months)
Design and deployment of credit strategies based on emerging loss trends
Creation of performance dashboards and tools to monitor KPIs and credit risk health
Collaboration with product and engineering teams to implement real-time credit decisioning
Delivery of presentations and reports to support strategic decisions at all levels
Key Competencies
Data Analytics & Visualization
Credit Rule Development
Strategic Communication
Cross-Functional Collaboration
Project Ownership & Execution
Interview Process
At-home screening assignment
Technical interview with senior team member
Final panel interview with hiring manager and team
Team Size: 5 members
Work Style: Close collaboration with senior data scientists initially, with room for independent ownership over time.
Focus Area: Reporting, visualization, and strategy design
This is a high-impact role at the intersection of data science, risk management, and business strategyperfect for professionals passionate about leveraging data to drive innovation in financial services.
Apply now to help shape the future of responsible credit risk management.
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.